Influence of preoperative leg pain and radiculopathy on outcomes in mono-segmental lumbar total disc replacement: results from a nationwide registry.

PURPOSE: Currently, many pre-conditions are regarded as relative or absolute contraindications for lumbar total disc replacement (TDR). Radiculopathy is one among them. In Switzerland it is left to the surgeon's discretion when to operate if he adheres to a list of pre-defined indications. Contraindications, however, are less clearly specified. We hypothesized that, the extent of pre-operative radiculopathy results in different benefits for patients treated with mono-segmental lumbar TDR. We used patient perceived leg pain and its correlation with physician recorded radiculopathy for creating the patient groups to be compared. METHODS: The present study is based on the dataset of SWISSspine, a government mandated health technology assessment registry. Between March 2005 and April 2009, 577 patients underwent either mono- or bi-segmental lumbar TDR, which was documented in a prospective observational multicenter mode. A total of 416 cases with a mono-segmental procedure were included in the study. The data collection consisted of pre-operative and follow-up data (physician based) and clinical outcomes (NASS form, EQ-5D). A receiver operating characteristic (ROC) analysis was conducted with patients' self-indicated leg pain and the surgeon-based diagnosis "radiculopathy", as marked on the case report forms. As a result, patients were divided into two groups according to the severity of leg pain. The two groups were compared with regard to the pre-operative patient characteristics and pre- and post-operative pain on Visual Analogue Scale (VAS) and quality of life using general linear modeling. RESULTS: The optimal ROC model revealed a leg pain threshold of 40 ≤ VAS > 40 for the absence or the presence of "radiculopathy". Demographics in the resulting two groups were well comparable. Applying this threshold, the mean pre-operative leg pain level was 16.5 points in group 1 and 68.1 points in group 2 (p < 0.001). Back pain levels differed less with 63.6 points in group 1 and 72.6 in group 2 (p < 0.001). Pre-operative quality of life showed considerable differences with an 0.44 EQ-5D score in group 1 and 0.29 in group 2 (p < 0.001, possible score range -0.6 to 1). At a mean follow-up time of 8 months, group 1 showed a mean leg pain improvement of 3.6 points and group 2 of 41.1 points (p < 0.001). Back pain relief was 35.6 and 39.1 points, respectively (p = 0.27). EQ-5D score improvement was 0.27 in group 1 and 0.41 in group 2 (p = 0.11). CONCLUSIONS: Patients labeled as having radiculopathy (group 2) do mostly have pre-operative leg pain levels ≥ 40. Applying this threshold, the patients with pre-operative leg pain do also have more severe back pain and a considerably lower quality of life. Their net benefit from the lumbar TDR is higher and they do have similar post-operative back and leg pain levels as well as the quality of life as patients without pre-operative leg pain. Although randomized controlled trials are required to confirm these findings, they put leg pain and radiculopathy into perspective as absolute contraindications for TDR.

Tissue biomarker development in a multicentre trial context: a feasibility study on the PETACC3 stage II and III colon cancer adjuvant treatment trial.

PURPOSE: We evaluated the feasibility of biomarker development in the context of multicenter clinical trials. EXPERIMENTAL DESIGN: Formalin-fixed, paraffin-embedded (FFPE) tissue samples were collected from a prospective adjuvant colon cancer trial (PETACC3). DNA was isolated from tumor as well as normal tissue and used for analysis of microsatellite instability, KRAS and BRAF genotyping, UGT1A1 genotyping, and loss of heterozygosity of 18 q loci. Immunohistochemistry was used to test expression of TERT, SMAD4, p53, and TYMS. Messenger RNA was retrieved and tested for use in expression profiling experiments. RESULTS: Of the 3,278 patients entered in the study, FFPE blocks were obtained from 1,564 patients coming from 368 different centers in 31 countries. In over 95% of the samples, genomic DNA tests yielded a reliable result. Of the immmunohistochemical tests, p53 and SMAD4 staining did best with reliable results in over 85% of the cases. TERT was the most problematic test with 46% of failures, mostly due to insufficient tissue processing quality. Good quality mRNA was obtained, usable in expression profiling experiments. CONCLUSIONS: Prospective clinical trials can be used as framework for biomarker development using routinely processed FFPE tissues. Our results support the notion that as a rule, translational studies based on FFPE should be included in prospective clinical trials.

Parametric imaging for characterizing focal liver lesions in contrast-enhanced ultrasound.

The differentiation between benign and malignant focal liver lesions plays an important role in diagnosis of liver disease and therapeutic planning of local or general disease. This differentiation, based on characterization, relies on the observation of the dynamic vascular patterns (DVP) of lesions with respect to adjacent parenchyma, and may be assessed during contrast-enhanced ultrasound imaging after a bolus injection. For instance, hemangiomas (i.e., benign lesions) exhibit hyper-enhanced signatures over time, whereas metastases (i.e., malignant lesions) frequently present hyperenhanced foci during the arterial phase and always become hypo-enhanced afterwards. The objective of this work was to develop a new parametric imaging technique, aimed at mapping the DVP signatures into a single image called a DVP parametric image, conceived as a diagnostic aid tool for characterizing lesion types. The methodology consisted in processing a time sequence of images (DICOM video data) using four consecutive steps: (1) pre-processing combining image motion correction and linearization to derive an echo-power signal, in each pixel, proportional to local contrast agent concentration over time; (2) signal modeling, by means of a curve-fitting optimization, to compute a difference signal in each pixel, as the subtraction of adjacent parenchyma kinetic from the echopower signal; (3) classification of difference signals; and (4) parametric image rendering to represent classified pixels as a support for diagnosis. DVP parametric imaging was the object of a clinical assessment on a total of 146 lesions, imaged using different medical ultrasound systems. The resulting sensitivity and specificity were 97% and 91%, respectively, which compare favorably with scores of 81 to 95% and 80 to 95% reported in medical literature for sensitivity and specificity, respectively.

Harvest managements and cultural practices in sugarcane

The presence of trash from the mechanical harvest of green cane on sugarcane plantations promotes changes in the agricultural management, for example, in the mechanical cultural practices of ratoon cane in-between the rows and nitrogen (N) fertilization. The goal of this study was to evaluate the performance of sugarcane in different harvest systems, associated to the mechanical cultural practices in interrows and N rates. The study was carried out on a sugarcane plantation in Sales Oliveira, São Paulo, Brazil, with the sugarcane variety SP81-3250, on soil classified as Acrudox, in a randomized block design with split-split plots and four replications. The main treatments consisted of harvest systems (harvesting green cane or burnt cane), the secondary treatment consisted of the mechanical cultural practices in the interrows and the tertiary treatments were N rates (0, 30, 60, 90, 120 and 160 kg ha-1), using ammonium nitrate (33 % N) as N source. The harvest systems did not differ in sugarcane yield (tons of cane per hectare - TCH), but in burnt cane, the pol percent and total sugar recovery (TSR) were higher. This could be explained by the higher quantity of plant impurities in the harvested raw material in the system without burning, which reduces the processing quality. Mechanical cultural practices in the interrows after harvest had no effect on cane yield and sugar quality, indicating that this operation can be omitted in areas with mechanical harvesting. The application of N fertilizer at rates of 88 and 144 kg ha-1 N, respectively, increased stalk height and TCH quadratically to the highest values for these variables. For the sugar yield per hectare (in pol %), N fertilization induced a linear increase.

Least limiting water range in assessing compaction in a Brazilian Cerrado latosol growing sugarcane

In the south-central region of Brazil, there is a trend toward reducing the sugarcane inter-harvest period and increasing traffic of heavy harvesting machinery on soil with high water content, which may intensify the compaction process. In this study, we assessed the structural changes of a distroferric Red Latosol (Oxisol) by monitoring soil water content as a function of the Least Limiting Water Range (LLWR) and quantified its effects on the crop yield and industrial quality of the first ratoon crop of sugarcane cultivars with different maturation cycles. Three cultivars (RB 83-5054, RB 84-5210 and RB 86-7515) were subjected to four levels of soil compaction brought about by a differing number of passes of a farm tractor (T0 = soil not trafficked, T2 = 2 passes, T10 = 10 passes, and T20 = 20 passes of the tractor in the same place) in a 3 × 4 factorial arrangement with three replications. The deleterious effects on the soil structure from the farm machinery traffic were limited to the surface layer (0-10 cm) of the inter-row area of the ratoon crop. The LLWR dropped to nearly zero after 20 tractor passes between the cane rows. We detected differences among the cultivars studied; cultivar RB 86-7515 stood out for its industrial processing quality, regardless of the level of soil compaction. Monitoring of soil moisture in the crop showed exposure to water stress conditions, although soil compaction did not affect the production variables of the sugarcane cultivars. We thus conclude that the absence of traffic on the plant row maintained suitable soil conditions for plant development and may have offset the harmful effects of soil compaction shown by the high values for bulk density between the rows of the sugarcane cultivars.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

Modelling ecological niches with support vector machines

1. The ecological niche is a fundamental biological concept. Modelling species' niches is central to numerous ecological applications, including predicting species invasions, identifying reservoirs for disease, nature reserve design and forecasting the effects of anthropogenic and natural climate change on species' ranges. 2. A computational analogue of Hutchinson's ecological niche concept (the multidimensional hyperspace of species' environmental requirements) is the support of the distribution of environments in which the species persist. Recently developed machine-learning algorithms can estimate the support of such high-dimensional distributions. We show how support vector machines can be used to map ecological niches using only observations of species presence to train distribution models for 106 species of woody plants and trees in a montane environment using up to nine environmental covariates. 3. We compared the accuracy of three methods that differ in their approaches to reducing model complexity. We tested models with independent observations of both species presence and species absence. We found that the simplest procedure, which uses all available variables and no pre-processing to reduce correlation, was best overall. Ecological niche models based on support vector machines are theoretically superior to models that rely on simulating pseudo-absence data and are comparable in empirical tests. 4. Synthesis and applications. Accurate species distribution models are crucial for effective environmental planning, management and conservation, and for unravelling the role of the environment in human health and welfare. Models based on distribution estimation rather than classification overcome theoretical and practical obstacles that pervade species distribution modelling. In particular, ecological niche models based on machine-learning algorithms for estimating the support of a statistical distribution provide a promising new approach to identifying species' potential distributions and to project changes in these distributions as a result of climate change, land use and landscape alteration.

Forecasting tourism demand to Catalonia: neural networks vs. time series models

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourismdemand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling relative to that of time seriesmethods at a regional level. Seasonality and volatility are important features of tourism data, which makes it a particularly favourable context in which to compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official statistical data of overnight stays and tourist arrivals fromall the different countries of origin to Catalonia from 2001 to 2009 is used in the study. When comparing the forecasting accuracy of the different techniques for different time horizons, autoregressive integrated moving average models outperform self-exciting threshold autoregressions and artificial neural network models, especially for shorter horizons. These results suggest that the there is a trade-off between the degree of pre-processing and the accuracy of the forecasts obtained with neural networks, which are more suitable in the presence of nonlinearity in the data. In spite of the significant differences between countries, which can be explained by different patterns of consumer behaviour,we also find that forecasts of tourist arrivals aremore accurate than forecasts of overnight stays.

Sulautetun moniprosessorijärjestelmän suunnittelu sähkömoottorien ohjaus- ja valvontatarpeisiin

Universal Converter (UNICON) –projektin osana suunniteltiin sähkömoottorikäyttöjen ohjaukseen ja mittaukseen soveltuva digitaaliseen signaaliprosessoriin (DSP) pohjautuva sulautettu järjestelmä. Riittävän laskentatehon varmistamiseksi päädyttiin käyttämään moniprosessorijärjestelmää. Prosessorijärjestelmässä käytettävää DSP-piiriä valittaessa valintaperusteina olivat piirien tarjoama prosessointiteho ja moniprosessorituki. Analog Devices:n SHARC-sarjan DSP-piirit täyttivät parhaiten asetetut vaatimukset: Ne tarjoavat tehokkaan käskykannan lisäksi suuren sisäisen muistin ja sisäänrakennetun moniprosessorituen. Järjestelmän mittalaiteluonteisuudesta johtuen keskeinen suunnitteluparametri oli luoda nopeat tiedonsiirtoyhteydet mittausantureilta DSP-järjestelmään. Tämä toteutettiin käyttäen ohjelmointavia FPGA-logiikkapiirejä digitaalimuotoisen mittausdatan vastaanotossa ja esikäsittelyssä. Tiedonsiirtoyhteys PC-tietokoneelle toteutettiin käyttäen erityistä liityntäkorttia DSP-järjestelmän ja PC-tietokoneen välillä. Liityntäkortin päätehtävänä on puskuroida siirrettävä data. Järjestelyllä estetään PC-tietokoneen vaikutus DSP-järjestelmän toimintaan, jotta kyetään takaamaan järjestelmän reaaliaikainen toiminta kaikissa olosuhteissa.

Feature-based matching of underwater images

This work investigates performance of recent feature-based matching techniques when applied to registration of underwater images. Matching methods are tested versus different contrast enhancing pre-processing of images. As a result of the performed experiments for various dominating in images underwater artifacts and present deformation, the outperforming preprocessing, detection and description methods are proposed

Aplicação de algoritmos genéticos na seleção de variáveis em espectroscopia no infravermelho médio: determinação simultânea de glicose, maltose e frutose

Genetic algorithm was used for variable selection in simultaneous determination of mixtures of glucose, maltose and fructose by mid infrared spectroscopy. Different models, using partial least squares (PLS) and multiple linear regression (MLR) with and without data pre-processing, were used. Based on the results obtained, it was verified that a simpler model (multiple linear regression with variable selection by genetic algorithm) produces results comparable to more complex methods (partial least squares). The relative errors obtained for the best model was around 3% for the sugar determination, which is acceptable for this kind of determination.

Correlação entre precursores e voláteis em café arábica brasileiro processado pelas vias seca, semiúmida e úmida e discriminação através da análise por componentes principais

The influence of pre-processing of arabica coffee beans on the composition of volatile precursors including sugars, chlorogenic acids, phenolics, proteins, aminoacids, trigonelline and fatty acids was assessed and correlated with volatiles formed during roasting. Reducing sugars and free aminoacids were highest for natural coffees whereas total sugars, chlorogenic acids and trigonelline were highest for washed coffees. The highest correlation was observed for total phenolics and volatile phenolics (R= 0.999). Experimental data were evaluated by Principal Components Analysis and results showed that washed coffees formed a distinct group in relation to semi-washed and natural coffees.

Akustisen emission anturin signaalin esikäsittelypiirin selvittäminen ja prototyypin toteuttaminen

Tämän työn tavoitteena oli selvittää ja toteuttaa esikäsittelypiirin prototyyppi akustisen emission anturin signaalille. Toteutettu esikäsittelypiiri toimii yksipuoleisella käyttöjännitteellä. Työssä käydään läpi esikäsittelypiirin suunnitteluun liittyvät vaiheet laskelmien ja simulaatioiden muodossa. Lisäksi työssä esitetään mittaustulokset esikäsittelypiirin toiminnasta.

Teurasjätteiden jalostaminen liikennepolttoaineiksi

Työssä määritettiin luokan 2 eläinperäisistä sivutuotteista liikennekäyttöön tuotettujen biodieselin ja biometaanin elinkaaren aikaiset kasvihuonekaasupäästöt ja tuotantoprosessien energiankulutukset perustuen kirjallisuuslähteistä saatuihin lähtötietoihin. Tätä kautta tutkittiin yhdistelmäprosessia, jossa tuotetaan molempia polttoaineita ja selvitettiin onko tällaisella tuotantotavalla mahdollista vähentää päästöjä ja parantaa polttoaineiden tuotannon energiatehokkuutta. Kasvihuone-kaasupäästöjen laskentamenetelmä pohjautuu direktiivissä 2009/28/EY annettuun ohjeistukseen ja eri kasvihuonekaasupäästöjen karakterisointi IPCC:n sadan vuoden tarkastelumalliin. Käytännön laskenta suoritettiin standardien SFS-EN ISO 14040 ja 14044 määrittelemän elinkaariarviointiselvityksen muodossa. Työssä käytetyn laskentamenetelmän ja tarkasteluun valittujen tuotanto-teknologioiden perusteella lasketut tulokset osoittavat, että yhdistelmäprosessilla ei saavuteta suurempia päästövähenemiä eikä parempaa energiatehokkuutta kuin nykyisin käytössä olevilla tuotantotavoilla. Tulokset ovat kuitenkin hyvin herkkiä laskennassa tehtyjen oletusten ja käytettyjen lähtötietojen vaihtelulle sekä valittujen laskentamenetelmien muutoksille. Suurin päästöjä ja energiankulutusta aiheuttava yksittäinen tekijä on kaikissa tuotejärjestelmissä luokan 2 sivutuotteiden esikäsittelyssä vaadittavaan steri-lointiin tarvittavan lämmön tuotanto. Tutkituissa tuotejärjestelmissä lämpö tuotetaan kokonaan tai osittain fossiilisilla polttoaineilla. Kasvihuone-kaasupäästöjä olisi mahdollista alentaa merkittävästi siirtymällä lämmön tuotannossa kokonaan uusiutuviin polttoaineisiin. Sterilointi on lain edellyttämä käsittelytapa ja siksi energiankulutusta on vallitsevissa olosuhteissa hyvin vaikea pienentää merkittävästi.

A decision support system for cost determination in grain storage facility operations

Many research works have being carried out on analyzing grain storage facility costs; however a few of them had taken into account the analysis of factors associated to all pre-processing and storage steps. The objective of this work was to develop a decision support system for determining the grain storage facility costs and utilization fees in grain storage facilities. The data of a CONAB storage facility located in Ponta Grossa - PR, Brazil, was used as input of the system developed to analyze its specific characteristics, such as amount of product received and stored throughout the year, hourly capacity of drying, cleaning, and receiving, and dispatch. By applying the decision support system, it was observed that the reception and expedition costs were exponentially reduced as the turnover rate of the storage increased. The cleaning and drying costs increased linearly with grain initial moisture. The storage cost increased exponentially as the occupancy rate of the storage facility decreased.